Title :
Prediction of financial time series based on information granulation
Author :
Xue, Mu-sen ; Gao, Hong
Author_Institution :
Coll. of Manage. & Econ., Tianjin Univ., Tianjin, China
Abstract :
The prediction of financial time series produced by the stock market has been the research focus of scholars. However, we can not accurately predict the fluctuations in the future in most cases. In this paper, we try to apply information granulation in the prediction of financial time series. First, we fuzzy grain the financial time series. Then, we use RBF neural network which has good ability of nonlinear mapping to predict future trend of fluctuations and fluctuating range. Simulation result shows that this method can accurately predict the trend of fluctuations and the fluctuating range, which can provide reliable reference for the decision makers of investment.
Keywords :
fuzzy set theory; granular computing; prediction theory; radial basis function networks; stock markets; time series; RBF neural network; financial time series prediction; fluctuating range; fluctuation trend; fuzzy grain; granular computing; information granulation; nonlinear mapping; stock market; words calculation; Fitting; Fluctuations; Forecasting; Simulation; Stock markets; Time series analysis; RBF neural network; information granulation; prediction;
Conference_Titel :
Industrial Engineering and Engineering Management (IE&EM), 2011 IEEE 18Th International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-61284-446-6
DOI :
10.1109/ICIEEM.2011.6035497